From installing a dedicated server to day-to-day maintenance, we provide a local AI agent environment you can trust even when handling confidential information.
Your input is never used for training, and a security-focused, in-house AI agent runs in a closed, safe environment, automatically blocking risky operations.
Public cloud AI services are convenient, but you can never fully rule out the concern that what you type gets used for training, or that your data ends up on servers outside your organization. For teams working with research data, patient records, or customer information that can't leave the building, that concern is a real barrier to adopting AI.
That's why we run AI (large language models) on a dedicated server and provide a "local AI agent" you can hand summarization, research, and everyday tasks to. It's built on the premise that your input is never used for training, and our own security-focused AI agent runs inside a closed, safe environment, automatically blocking risky operations — so you can put AI to work even on sensitive information with confidence.
We handle everything end to end: selecting and setting up the server, initial configuration, and ongoing monitoring and updates after launch.
We design a server configuration matched to your use case and confidentiality needs, and handle everything from installation and initial setup through ongoing monitoring and updates after launch.
We build on the premise that your input is never used to train the model. Even conversations involving confidential information stay entirely within a closed environment, without ever reaching an outside service.
Our own security-focused AI agent runs inside a closed, safe environment, preventing any effect from reaching outside that environment while automatically blocking risky operations.
If you'd rather operate in an environment isolated from external networks, we install a dedicated server on-site, in a configuration where no data ever leaves the building.
If running your own server isn't practical, we build a dedicated tenant in the cloud instead. It doesn't share resources with other tenants, and the same "never used for training" design and closed, protected environment apply just as they would on-premise.
We're happy to start with a proposal tailored to your use case and confidentiality needs.